Consumptible identification system and method

ABSTRACT

A consumptible identification system for use with a computer network includes a need prioritization module adapted to obtain a prioritization of consumer needs associated with a consumptible category from a particular consumer, wherein the prioritization expresses a preference of the particular consumer pertaining to at least one need associated with the category relative to at least one other need associated with the category. It further includes a matching module adapted to match a comsumptible identity to the particular consumer based on the prioritization of consumer needs and relationships between consumer needs and consumptible identities associated with the consumptible category. In addition, it has a user interface adapted to communicate the consumptible identity to the particular consumer.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.10/449,860 filed on May 30, 2003. The disclosure of the aboveapplication is incorporated herein by reference.

FIELD OF THE INVENTION

The present invention generally relates to computer networked consumerand seller matching systems and methods, and particularly relates toidentification of a consumptible based on a prioritization of consumerneeds relating to the consumptible that expresses a relative referenceof the consumer pertaining to the needs.

BACKGROUND OF THE INVENTION

Today's Internet search tools may be successful at helping a consumerfind a consumptible, such as a product or service, according to specificconsumptible attributes. For example, a consumer accessing a searchableweb site providing listings for houses may obtain a list of homes in aconsumer-specified area that match search criteria for price, number ofbedrooms, number of baths, square footage, and similar search criteriathat are objectively measurable in a directly quantifiable fashion.Similarly, one may expect in other domains to obtain, for example, anidentification of an automobile based on price, horsepower, wheelbase,torque, towing capacity, and similar criteria that are objectivelymeasurable in a directly quantifiable fashion. Today's tools, however,suffer from the need to require a particular consumer to identify anappropriate set of consumptible attributes with specific values and/orvalue ranges when searching for a matching consumptible. As a result,today's tools fail to accurately match a consumptible to a particularconsumer's subjectively perceptible needs relating to consumer benefitsderived from one or more consumptible attributes.

Today's Internet search tools are unsuitable for assisting consumers inmaking decisions because consumers needing assistance in identifying aconsumptible that meets their individual needs typically may not beexperts in fields relating to the corresponding consumptible categories.As a result, they typically lack the expertise required to translatetheir subjectively perceived needs relating to customer benefits intothe consumptible attributes and associated performance values from whichthose benefits are derived. Therefore, the need remains for aconsumptible identification system and method that successfully matchesa consumptible identity to a particular consumer based on aprioritization of consumer needs and expertly identified relationshipsbetween consumer needs and consumptible identities associated with theconsumptible category. The present invention fulfills this need.

SUMMARY OF THE INVENTION

In accordance with the present invention, a consumptible identificationsystem for use with a computer network includes a need prioritizationmodule adapted to obtain a prioritization of consumer needs associatedwith a consumptible category from a particular consumer, wherein theprioritization expresses a preference of the particular consumerpertaining to at least one need associated with the category relative toat least one other need associated with the category. It furtherincludes a matching module adapted to match a consumptible identity tothe particular consumer based on the prioritization of consumer needsand relationships between consumer needs and consumptible identitiesassociated with the consumptible category. In addition, it has a userinterface adapted to communicate the consumptible identity to theparticular consumer.

The present invention is advantageous over previous networked consumerassistance tools in that it may identify consumptibles based on needs ofparticular consumers without requiring that the consumer translate theirindividual needs into specific values of consumptible attributes. It isfurther advantageous in that it may prompt consumers to visually compareconsumer needs for a given consumptible category, thereby obtaining aconsumer-specific prioritization of expertly identified needs that mayhave been expertly correlated to existing consumptible performanceattributes and consumptibles. The foregoing advantage may be furtherdeveloped by permitting a consumer to select or otherwise specify asubset of predetermined needs from a superset of predetermined needs forthe consumptible category, thereby quickly focusing the need comparisonand consumptible identification procedure. The present invention maystill be further advantageous in that it may allow experts to separatelycontrol for variability in consumer needs and functionally contextualfactors relating to consumptible attributes. The present invention mayyet further be advantageous in that it may encourage consumers toprovide full specifications for predefined consumptible attributes,survey consumer needs across various consumer categories, obtaininformation relating to contextual utility of consumptible attributes,and monitor performance of particular consumptibles; this aggregatedinformation may be useful to sellers for further consumptibledevelopment. Yet further areas of applicability of the present inventionwill become apparent from the detailed description provided hereinafter.It should be understood that the detailed description and specificexamples, while indicating the preferred embodiment of the invention,are intended for purposes of illustration only and are not intended tolimit the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description and the accompanying drawings, wherein:

FIG. 1 is a partial-perspective block diagram of the system of thepresent invention;

FIG. 2 is a block diagram depicting system processes according to arelationship acquisition procedure in accordance with the presentinvention;

FIG. 3A is a block diagram depicting need to attribute relationshipstrengths stored in a consumptible rating database for use with thepresent invention;

FIG. 3B is a block diagram depicting relative consumptible attributeperformance values stored in a consumptible rating database inaccordance with the present invention;

FIG. 4A is a data flow diagram depicting data progression in accordancewith the present invention;

FIG. 4B is a graph depicting a utility curve in accordance with thepresent invention;

FIG. 4C is a block diagram depicting relative consumptible attributeperformance values generated by use of the utility curve of FIG. 4B;

FIG. 5 is a block diagram depicting system processes according to aconsumptible information acquisition process in accordance with thepresent invention;

FIG. 6 is a block diagram depicting system processes according to aconsumptible identification procedure in accordance with the presentinvention; and

FIG. 7 is a flow diagram depicting a method of consumptibleidentification for use with a computer network in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiment(s) is merelyexemplary in nature and is in no way intended to limit the invention,its application, or uses.

FIG. 1 illustrates one embodiment of the system according to the presentinvention implemented with communications network 10, such as theInternet, that may connect system server 12 with plurality of clientterminals 14, which may include expert computer 16, seller computer 18,and consumer computer 20. Server 12 may run software providing categoryselection interface 22, which may be adapted to allow a user to select aconsumptible category, and a plurality of interface modules 24, 26, and28, which may allow consumers, sellers, and experts to interact withvarious databases 30, 32, 34, and 36. Consumer interface module 24, forexample, may permits a consumer using consumer computer 20 to create auser account in user accounts database 30 and store consumer categorydata, such as demographics, psychographics, and ethnograhics, therein.It also may allow the consumer to search consumptible rating database 36by prioritizing consumer needs associated with a consumer-specifiedcategory, and store data relating to consumer needs in aggregated datadatabase 32. Similarly, seller interface module 26 may permit a sellerusing seller computer 18 to create an account in user accounts database30 and store a consumptible identity and detailed specs for a particularconsumptible in consumptible information database 34. Further, expertinterface module 28 may permit an expert using expert computer 16 toaccess consumptible information database 34 in a consumptible categorydesignated in an expert account of user accounts database 30, and toprovide rating scales and/or relationships to consumptible ratingdatabase 36 for the corresponding consumptible category. Categorizedweights reflecting expert knowledge relating to a consumptible categoryand stored in a corresponding expert account may control the degree towhich an opinion of a particular expert influences a particularcategory.

FIG. 2 illustrates a sub-embodiment of a relationship acquisitionprocess involving experts in accordance with the present invention. Forexample, category selection interface 22 of relationship acquisitionmodule 38 may obtain consumptible categories 39 from consumptible ratingdatabase 36 and communicate available categories 40 to an expert viauser interface 42. The expert may respond via interface 42 with acategory selection 44, and a selected category 46 may in turn becommunicated to rating scale acquisition module 48. Module 48 mayfurther be receptive of expert-defined consumer needs 50 and measurableconsumptible attributes 52A for selected category 46, and needs andattributes 54 may be output in the form of a rating scale illustratedwith reference to FIG. 3A. Therein, consumer needs may related toconsumptible attributes as rows and columns in matrix 56 for theselected category, and this rating scale may stored in consumptiblerating database 36 (FIG. 2) of data store 58, and further communicatedto need-attribute relationship acquisition module 60. Module 60, inturn, may communicate combinatorial need-attribute pairs 62 to theexpert with a request for a numerical rating 64 expressing an expertjudgment of a relationship strength expressing how well a consumptibleattribute meets a consumer need. Information relating needs toattributes 66 may then be stored as relationships 67 (FIG. 3) incorresponding cells 68 of matrix 56.

FIG. 5 illustrates a sub-embodiment of a consumptible informationacquisition process involving sellers according to the presentinvention. Therein, category selection interface 22 of inventoryaccumulator 70 may communicate consumptible categories 41 to a seller asavailable categories 40 via user interface 42. The seller may respondwith a category selection 44, and selected category 46 may becommunicated to consumptible information acquisition module 72.Corresponding measurable consumptible category attributes 52A ofconsumptible rating database 36 may be retrieved by module 72 andcommunicated to the seller at 52B via interface 42. In response to theresulting prompts, the seller may provide detailed consumptiblespecifications 74 for each consumptible attribute associated with theselected category, as well as the consumptible identity 76. Acquiredconsumptible information 78 may then be stored in consumptibleinformation database 34 of data store 58.

Returning to FIG. 2, a revisiting expert and/or subsequentlycontributing expert selecting a consumptible category 46 havingconsumptible information already stored in consumptible informationdatabase 34 may further receive combinatorial attribute and consumptibleidentity pairs 80 for selected category 46 from attribute-consumptiblerelationship acquisition module 82 based on attributes 52B andconsumptible information 78 of consumptible information database 34. Theexpert may further receive detailed specifications for each attributeand consumptible identity associated with selected category 46 based onconsumptible information 78. The expert may respond to the resultingprompts with a numerical rating 84 indicating relative, contextualutility of a particular consumptible's actual performance value withrespect to a consumptible attribute of the category. Informationrelating attributes to consumptible identities 86 may then be stored asrelationships 88 (FIG. 3) in corresponding cells 90 of matrix 92associated with selected category 46 (FIG. 2) in consumptible ratingdatabase 36.

Information 86 respective of a particular attribute may constitute autility curve. For example, if a consumptible attribute corresponds totowing capacity of a vehicle, and a number of classes of recreationalequipment increases exponentially over a linear weight range, and thendecreases logarithmically over a higher weight range, then thisinformation may be reflected in the expertly defined relationshipsbetween towing capacity and consumptible identifications. Thus, avehicle able to tow most recreational vehicles in addition to mosttrailers may have twice the score respective to towing capacity comparedto a vehicle with ninety-percent of the same towing capacity that canonly haul small recreational equipment and one class of moving trailer.Similarly, a vehicle with ten times the towing capacity that can onlytow ten percent more classes of equipment may have only a slightlyhigher score respective to towing capacity. As a result, the expert maycontrol for relative utility of consumptibles in a quantifiablefunctional context independently of subjectively perceived consumerneeds.

Alternatively, experts may be asked to develop an actual utility curve136 (FIG. 4B). Accumulated data from the weighted experts may becompiled into a map or table as graphed in FIG. 4B. Then, a function maybe implemented to populate a row of a matrix 42A for a consumptiblecategory attribute, such as towing capacity of a vehicle, relative toparticular vehicle models V1-V4 (FIG. 4B) having actual performancevalues specified for the attribute; the actual performance values may bespecified, for example, by sellers at a time of registration of thevehicle models in association with the consumptible category. As aresult, consumptible categories 40 (FIG. 4A) may point to consumptibleidentities 76, which may in turn have actual performance values 138specified for the consumptible attributes of the categories according tospecifications provided by sellers. These actual performance values maybe filtered through an expertly provided utility curve 136 and/orinterpreted by experts based on relative utility to arrive at relativeconsumptible attribute performance values 138 specified for theconsumptible attributes of the categories relative to the consumptibleidentities of the categories. In turn, need to attribute relationshipstrengths 140 may be used in conjunction with the relative consumptibleattribute performance values 138 to identify prioritized consumptibleidentities 142 for a category based on prioritized consumer needs 144for the category.

FIG. 6 illustrates a sub-embodiment of a consumptible identificationprocedure according to the present invention. Therein, a consumer mayreceive a list of available consumptible categories 40 via userinterface 42 from category selection interface 22 based on designatedconsumptible categories 41 of data store 58. The consumer's categoryselection 44 may result in communication of selected category 46 to needprioritization module 88 and matching function 89 of matching module 91.Need prioritization module 88 may communicate combinatorial need pairs93 to the user based on selected category 46 and needs 94 associatedwith selected category 46 according to consumptible rating database 36of data store 58. Combinatorial need pairs may provide a rating scale tothe particular consumer that permits the particular consumer to performneed to need comparisons with respect to the combinatorial pairs ofconsumer needs using, for example, drag bars permitting the consumer tovisually and intuitively illustrate a proportion of priority dividedbetween competing consumer needs. The resulting comparison selections 96communicated to need prioritization module 88 are particularly wellsuited to obtaining ratio scale numbers that may be used to compute theprioritization 98 of consumer needs based on the need to needcomparisons as a row average of normalized columns, and theprioritization of consumer needs may further be communicated to matchingfunction 89. In turn, matching function 89 may access consumptiblerating database 36 of data store 58 based on selected category 46 andprioritization 98, and may obtain a consumer-dependent rating ofconsumptibles 100 for the category that may be communicated to theconsumer via interface 42.

In an example of operation according to the present invention, aconsumer selecting a consumptible category corresponding to“automobiles” may be presented with a checklist including dozens ofselectable consumer needs relating to the “automobiles” category. Inresponse, the consumer may select four of these needs, including “lowprice”, “easy to drive”, “stylish”, and “reliable”. The consumer maynext be presented with a visual representation of combinatorial pairs ofconsumer needs with color coded drag bars expressing a bivalentspectrum. The consumer may drag the bars left or right for eachcombinatorial pair to express a priority-based distribution ofcomparative importance value for each need compared to every other needof the category. With four needs, there are six combinatorial pairs. Arow average may be computed for each consumer need based on thecomparisons, and the “need priority” column of matrix 56 (FIG. 3) may bepopulated with values representing a percentage of priority placed onthe corresponding consumer needs by the particular consumer. Thesescalar values may then be multiplied by scalar values stored in cells 68in accordance with relationships 67, and the column results for eachattribute, such as “drag coefficient”, “horse power”, “price with optionpackage”, and “lemon law claims per annum”, may be added together toobtain consumer-specific priority values which populate the “attributepriority” row. These attribute priorities may then be used to populatethe attribute priorities column of matrix 92, and may similarly bemultiplied by scalar values of cells 90 and added together for eachconsumptible identity to obtain consumer-specific priority values thatmay populate the “consumptible priority” row. These consumptiblepriorities may then be used as consumptible ratings, and consumptibleidentities may be communicated to the consumer together with theirratings, a bar graph visually depicting their ratings, and a pie chartvisually depicting the computed values representing percentage ofpriority placed on the corresponding consumer needs by the particularconsumer that resulted in the consumer-specific ratings.

FIG. 7 illustrates an embodiment of a method of the present invention.Beginning at 102 the method may proceed with development of consumerneeds related to consumptible attributes for one or more consumptiblecategories at step 104. Thus, consumptible categories may be designatedat step 106, and expert identifications of consumptible attributes andconsumer needs may be obtained for each designated category at step 108.Step 108 may be performed separately for each category, with a primaryexpert for the category defining the columns and rows of a resultingmatrix. The primary expert for each category may also provide initialrelationship data for the category that relate the consumer needs to theconsumptible attributes in step 110. Then, additional experts mayprovide more relationship data in step 110 for the category that may beused to adjust the initial relationship data according to weightedvalues assigned to the contributing experts based on their knowledgewith respect to the particular consumptible category. Meanwhile, theattributes defined for a consumptible category may be used to prompt aseller of a consumptible in the category for detailed consumptiblespecifications for each attribute at step 112. Then, the specificationsmay be used by knowledgeable experts in step 114 when obtainingrelationship data from the experts relating consumptible attributes toconsumptible identities based on relative utility of performance valueswith respect to the consumptible category attributes. These experts maybe different from the experts who provide relationships between consumerneeds and consumptible attributes, and may be employed to developmentutility curves for various consumptible attributes relating actualperformance value to actual functional value within a market context aspreviously discussed. Then, the relationships between the consumptibleattributes and the consumptible identities may be mapped in an automatedfashion using the performance values expressed in the detailedspecifications to obtain a relative functional value using the utilitycurve that identifies a relationship between the consumptible identityand the consumptible attribute.

With relationships between consumer needs and consumptible identitiesexpertly defined at 104, consumptible identities may be matched toparticular consumers based on a consumer-specific prioritization ofconsumer needs at step 116. Accordingly, need to need comparisons ofcombinatorial pairs of consumer needs may be obtained from individualconsumers at step 118, and consumer-specific prioritizations of consumerneeds may be computed at step 120 based on the need to need comparisons.Next, consumer-specific prioritizations of consumptible attributes maybe computed at step 122 based on the consumer specific prioritizationsof consumer needs and expertly defined relationships between consumerneeds and consumptible attributes. Then, individual existingconsumptibles may be rated for individual consumers by computingconsumer-specific prioritizations for consumptible identities at step124 based on the consumer-specific prioritizations of consumptibleattributes and the expertly defined relationships between theconsumptible attributes and the consumptible identities. Theseconsumer-specific ratings may then be communicated to the individualconsumers at step 126, with the method ending at 128.

The method of the present invention have further steps directed to theconsumptible development side, such as obtaining consumer categoryinformation (demographics, psychographics, ethnograhics) at step 130.Also, data may be aggregated at step 132, including consumer categoryinformation obtained in step 130 and consumer needs obtained in step116, and this aggregated data may be used at step 134 to assist inredeveloping existing consumptibles and/or developing new consumptibles.For example, the consumer needs and consumer category information may beused to obtain consumer category specific prioritizations of consumerneeds for various consumptible categories. Further, performance of aparticular consumptible relative to commonly expressed consumer needsmay be obtained on step 116 and aggregated in step 132, and thisinformation may be used in step 134 to identify consumptibles in need ofredevelopment. Still further, the detailed specifications obtained instep 104 may be aggregated at step 132 and used to provide informationon existing consumptible attributes that developers may otherwise haveto obtain by other means. Yet further, the expertly developed matricesconstructed in step 104 to relate consumer needs to consumptibleattributes can be aggregated at step 132 and used as part of a House ofQuality as known in the art of Quality Function Deployment (QFD) toassist in developing consumptibles. The utility curve expressed in therelationships obtained in step 114 may further be used in a cost-benefitanalysis to identify an optimal consumptible attribute value in a givenmarket context.

It is important to note that various alternative embodiments of thepresent invention may be implemented to service consumers of varyinglevels of expertise relating to one or more consumptible categories. Asa result, the present invention may be implemented to allow a consumerto specify a specific and/or range of performance values for one or moreconsumptible attributes, and combine these limitations with theprioritization of needs relating to consumer benefits derived from oneor more consumptible attributes. For example, a consumer may beinitially presented with a list of consumptible needs, such as doors,comfort, speed, and towing capacity, for a selected category, such asautomobiles. In this example, the consumer may be allowed to select toexpress a specific number of doors for the vehicle, such as four, andfurther to select to compare two of the needs, such as comfort andspeed. In this case, the matching module may filter the consumptibleidentities of the category by constructing, on the fly, a matrix ofautomobile models having four doors related to all of the consumptibleattributes for the category. The automobile models may subsequently berelated to the attributes using the appropriate utility curves. Theprioritization of the two needs may then be related to the attributes,and a prioritization of automobiles having four doors obtained. Itshould be readily understood that equivalent filtering methods mayinclude rescoring of prioritized consumptible identities based on thespecified performance value, and/or other ways of renderingnon-conforming consumptible identities ineligible.

The description of the invention is merely exemplary in nature and,thus, variations that do not depart from the gist of the invention areintended to be within the scope of the invention. For example, thepresent invention may be less advantageously accomplished by relatingconsumer needs directly to consumptible identities, without the interimsteps of relating to consumptible attributes and using utility curves.Also, actual performance values of consumptibles may alternatively belinearly mapped to consumptible category attributes. Further, theprioritizations of consumer needs may be accomplished by other meansthan a need to need comparison, and use of a pie chart to display theneeds with pie piece dividers that can be dragged to adjust thepriorities is another example of an intuitive graphical user interfacefor obtaining the consumer-specific priorities. Still further, variousalternative embodiments may communicate the results in additional ways,such as by normalizing priorities associated with consumptibleattributes and/or consumptible identities and graphically displayingthem to consumers as pie charts. Still further, although two-dimensionalmatrices may be used to visually communicate the processes of thepresent invention, it should be readily understood that various datastructures and complementary referencing algorithms can be employed toaccomplish the present invention in a variety of ways, as with lookuptables and/or vectors with three or more dimensions. Yet further, thepresent invention may be employed in various market contexts including,for example, contract evaluation. In this embodiment, equipmentspecifications may listed on rows of a matrix as consumer needs, anddesign elements for meeting the consumptible specifications that make upa given proposal may be listed on the columns as consumptibleattributes. In this context, the consumptible category may correspondsto a contract to supply new equipment, and the proposal submittingentity can perform the relationship matrix work. However, the consumer,the one issuing the Request For Proposal (RFP) and needing the newequipment, may be able to have their experts also perform relationshipmatrix work to judge how well a proposal meets the RFP. Such variationsare not to be regarded as a departure from the spirit and scope of theinvention.

1. A system for recommending a product identity to a user from aplurality of product identities, comprising: a product database storingquantifiable product attributes for a category of goods, the category ofgoods having a plurality of product identities belonging thereto, eachproduct identity having a set of quantifiable product attributesassociated therewith, wherein each quantifiable product attribute has aquantification; a relationship data structure defining a plurality ofrelationships between the quantifiable product attributes belonging tothe category of goods and subjective properties relating to the categoryof goods, wherein a relationship represents a correlation of one of thequantifiable product attributes to one of the subjective propertiesrelating the category of goods, wherein a plurality of differentpredefined subjective properties relate to the category of good; a userinterface that displays the subjective properties relating to thecategory of goods and that receives from the user an amount ofimportance for at least two of the subjective properties relating to thecategory of good; and a prioritization module that determines a productidentity recommendation for the user based on the inputted amount ofimportance of subjective properties relating to category of goods by:calculating prioritization scores of the product attributes using theinputted amount of importance of the at least two subjective propertiesand the relationship data structure; and calculating rankings of thedifferent product identities using the calculated prioritization scoresof the product attributes and the quantifications of the productattributes of the product identities stored in said product database;and determining a product identity recommendation based on the rankingsof the different product identities.
 2. The system of claim 1 whereinthe user interface displays the subjective properties to the user andthe user indicates an amount of importance of at least two of thesubjective properties with respect to other subjective propertiesrelating to the category of goods.
 3. The system of claim 2 wherein theprioritization module calculates prioritization score for each productattribute by: a) determining a percentage of importance of thesubjective properties using the amounts of importance of the subjectiveproperties with respect to the other subjective properties; b)multiplying the percentage of importance of each of the subjectiveproperties with the corresponding correlation between the subjectiveproperty and the product attribute whose prioritization score is beingcalculated; and c) summing up the products calculated in step b) foreach product attribute.
 4. The system of claim 1 wherein for eachproduct identity, the prioritization scores for the quantifiable productattributes are multiplied by the corresponding quantifications of thequantifiable product attribute of the product identity and the resultingproducts are summed, wherein the resulting sums for the productidentities are compared to one another to determine a ranking of productidentities.
 5. The system of claim 1 further comprising aproperty-attribute relationship acquisition module that communicatessubjective property and quantifiable product attribute pairs to anexpert and that receives the correlation between the communicatedsubjective property and the quantifiable product attribute pair from theexpert, wherein the relationships between the quantifiable productattributes and subjective properties are defined by the expert.
 6. Thesystem of claim 5 wherein the relationship data structure is a matrixwhose elements represent the correlations of the quantifiable productattributes to the subjective properties.
 7. The system of claim 1further comprising a product identity acquisition module that receives apotential product identity from a source of a product having saidpotential product identity and receives the at least some of thequantifiable product attributes of said potential product identity fromsaid producer, wherein said potential product identity becomes one ofthe product identities of the plurality of product identities.
 8. Thesystem of claim 1 further comprising an attribute-identity acquisitionmodule that communicates at least one product identity and aquantifiable product attribute associated with said communicated productidentities to an expert and receives quantifications for thequantifiable product attributes of the communicated product identities,wherein said quantifications are stored in said product database.
 9. Thesystem of claim 8 wherein the quantification is a numerical ratingindicating an absolute or relative performance value for the productidentity with respect to other product identities.
 10. The system ofclaim 8 wherein the quantifications of the quantifiable productattributes of the product identities within the category of goods aredefined by utility curves.
 11. The system of claim 1 wherein thecategory goods is selected by the user from a plurality of categories ofgoods.
 12. A method for recommending a product identity havingquantifiable product attributes from a plurality of different productidentities to a consumer comprising: presenting, on a display unit, aplurality of different subjective properties relating to a category ofgoods to a user, wherein the plurality of different product identitiesbelong to the category of goods and the plurality of differentsubjective properties are properties of the plurality of differentproduct identities; receiving, via a user interface, user inputindicating amounts of importance of the subjective properties to theuser; calculating, on a processor, prioritization scores of quantifiableproduct attributes for the user using on the inputted amount ofimportance of each subjective property and a plurality of relationshipsbetween the quantifiable product attributes associated with theplurality of different product identities and the subjective propertiesrelating to the category of goods, wherein a relationship represents acorrelation of one of the quantifiable product attributes to one of thesubjective properties; calculating, on the processor, a product rankingfor each product in the plurality of different products using on theprioritization scores of product attributes and quantifications of theproduct attributes for each product identity of the plurality ofdifferent product identities; and presenting to the user a recommendedproduct based on the product rankings for each product.
 13. The methodof claim 12 wherein the user interface displays the subjectiveproperties to the user and the user indicates an amount of importance ofat least two of the subjective properties with respect to othersubjective properties relating to the category of goods.
 14. The methodof claim 12 wherein calculating the prioritizations scores furthercomprises: a) determining a percentage of importance of the subjectiveproperties from the amounts of importance; b) multiplying the percentageof importance of each of the subjective properties with thecorresponding correlation between the subjective property and theproduct attribute whose prioritization score is being calculated; and c)summing up the products calculated in step b) for each quantifiableattribute product attribute.
 15. The method of claim 14 wherein for eachproduct identity, the prioritization scores for the quantifiable productattributes are multiplied by the corresponding quantifications of thequantifiable product attribute of the product identity and the resultingproducts are combined, wherein the resulting values for the productidentities are compared to one another to determine a product ranking ofproduct identities.
 16. The method of claim 12 further comprisingcommunicating a plurality of categories of goods to the user andreceiving the category of goods from the plurality of categories ofgoods from the user, via the user interface.
 17. The method of claim 12further comprising communicating pairs of subjective properties andquantifiable product attributes to an expert and receiving thecorrelation between the communicated subjective property and thequantifiable product attribute from the expert, wherein therelationships between the quantifiable product attributes belonging tothe category of goods and subjective properties relating to the categoryof goods are defined by the expert and loaded onto a computer readablemedium associated with said system.
 18. The method of claim 12 furthercomprising receiving a product identity from a producer of a producthaving said product identity and receiving at least some of thequantifiable product attributes of the product identity from saidproducer.
 19. The method of claim 12 wherein the quantification is anumerical rating indicating a relative performance value for the productidentity with respect to other product identities.
 20. The method ofclaim 12 wherein the user is presented with the means to transact apurchase for the product identities which receive a ranking.